A trend of increasing rates of hepatocellular carcinoma (HCC) has been reported worldwide, that is related to the high prevalence of hepatitis C virus (HCV) infection in the population. Better means for HCC diagnosis are urgently needed. Our prior studies provided evidence for an association between the etiology of the underlying liver disease and differences in patterns of gene/protein expression in HCC. They also offered new insights into protein isoforms that are potentially important in the development of HCC. We recently developed a method to comprehensively and quantitatively profile the proteome of a complex sample and we have applied this method to the liver and to plasma. This method, based on extensive fractionation of intact proteins, resulted in the identification of approximately 9,000 proteins in the liver, identified with high confidence and including low-abundance proteins such as cytokines, chemokines and receptors. An abundance score based on spectral counts was attributed to each identified protein. The calculated abundance scores appeared to be a good estimate of protein abundance. In the plasma, numerous low-abundance proteins in the biomarker concentration range (pg/ml) were identified and proteins specific to disease stage (fibrosis and early HCC) were identified in liver tissue as well as in plasma. Interestingly, there was no correlation between the abundance changes observed in the tissues and the abundance changes observed in the plasma for selective proteins changing with disease stage. In conclusion, this method reached a depth in proteomic profiling not previously reported for complex biological mixtures such as mammalian tissue and plasma, allowed for the identification of protein changes associated with disease and suggested that tissue-based discovery and plasma-based discovery studies may lead to different results. The purpose of this proposal is to utilize this method for the identification of protein biomarkers for HCV-related HCC that could be used for early detection and diagnosis. We will apply this approach to identify proteins and their isoforms that differ in expression levels between plasma obtained from patients with HCV-related cirrhosis that have recently progressed to HCC and patients with HCV-related cirrhosis with no HCC. The most promising candidates identified in the discovery component of this research will be targeted for validation. We will establish the sensitivity and specificity of these protein biomarkers individually and in combination, for detecting HCC early.